Towards a quantitative theory of performance and success

Performance, representing the objectively measurable achievements in a certain domain of activity, like the publication record of a writer or the winning record of an athlete, captures the actions of an individual entity. In contrast, success, captured by impact or visibility, is a collective measure, representing a community’s reaction and acceptance of an individual entity’s performance. We are often driven by the belief that the detection of extraordinary performance is sufficient to predict exceptional success. However, the link between these two measures, while often taken for granted, is actually far from being understood. Indeed, even experts of performance assessment are notoriously bad at predicting long-term success. Nevertheless, differently from performance, success is quantifiable and predictable: given its collective nature, its signatures can be uncovered from the many pieces of data around us using novel tools from network and data science.

In this talk I will show how we can quantify and predict success in a variety of fields. I will discuss the role of luck in achieving success, and will address the relation between performance and success in a variety of settings, highlighting the challenges of gauging performance through success.